Estimated liquidation zones by leverage 5x/10x/20x ($0.003 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| payment | No | Optional. Base64 x402 payment payload you signed yourself (ERC-3009 TransferWithAuthorization, USDC on Base). Call without it once to receive the payment requirements, sign those, then call again with this argument. This server forwards the payload and never holds a key. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / paymentAdded value: +{
+ "description": "Optional. Base64 x402 payment payload you signed yourself (ERC-3009 TransferWithAuthorization, USDC on Base). Call without it once to receive the payment requirements, sign those, then call again with this argument. This server forwards the payload and never holds a key.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of explaining behavioral expectations. It hints at cost with '$0.003 USDC' and labels the result as 'estimated', but it does not disclose the paid x402 flow, the need to call once without payment, or whether this operation spends funds before returning data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely compact and front-loaded: it names the subject, the scope, and the price with no wasted words. The parenthetical cost is terse but effectively communicates the paid aspect.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is conceptually simple and has only one optional parameter, but the description omits the underlying asset or outcome format and leaves the payment authorization flow entirely to the schema. It is minimally viable but an agent might not know the tool requires payment before a meaningful response, or what shape the estimated liquidation zones take.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the payment parameter's own description thoroughly documents the handshake and security properties. The main description adds little beyond the '$0.003 USDC' pricing hint, so it provides no extra parameter meaning on top of a strong schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifically states the resource ('liquidation zones') and the key dimension ('by leverage 5x/10x/20x'), which meaningfully expands on the tool name. It does not explicitly include a verb like 'returns' or 'gets', and it does not distinguish it from get_support_resistance or other price-level siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to prefer this tool over alternatives, no exclusions, and no prerequisites described. The description's mention of specific leverage levels implies a use case, but it never states a decision rule or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target clearly distinct metrics, but the paid/free sample pairs (get_crypto_prices/try_crypto_prices, etc.) and overlapping summary tools (get_market_overview, get_market_pulse, get_overnight_risk_brief) create some selection ambiguity. Descriptions list components, so an agent can disambiguate with effort, but the boundaries between bundles and single-purpose tools are not always obvious.
Tool names consistently follow a verb_noun pattern: get_ for data retrieval, try_ for free samples, and watch_condition for persistent monitoring. All names use lowercase snake_case with no mixed conventions, making the naming predictable and easy to navigate.
34 tools is well above the comfortable range for a typical MCP server and feels heavy even for a broad crypto data domain. The count is inflated by paid/free sample duplicates and multiple bundle variants that could have been consolidated.
The surface covers a wide range of crypto data: prices, funding, sentiment, arbitrage, derivatives, on-chain metrics, signal history, and monitoring. Minor gaps exist—such as no obvious generic signal discovery tool or order-book/trade-level data—but the core domain of market data with checkable records is thoroughly served.